The purpose of this thesis is to research the presence of dark patterns on the websites of selected airlines and to evaluate the possibility of their automatic detection using various approaches. The theoretical part is based on an established classification of dark patterns and discusses their impact on both users and companies. In the empirical part, a comparative analysis of manual analysis, analysis with the ChatGPT tool, and a self-developed browser extension is performed. Each method has its advantages and disadvantages. In this study, manual analysis proved to be the most reliable, but a combination of different approaches is advisable for the most comprehensive results.
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